April 2019 arXiv papers — page 79

Juan Liu, Kevin M. Koch

Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to infer estimates of local tissue magnetism (magnetic susceptibility), which has been shown useful to provide novel image contrast and as biomarkers of abnormal tissue. QSM requires addressing a challenging post-processing problem: filtering of image phase estimates and inversion of the pha

Tohru Kawarabayashi, Hideo Aoki, Yasuhiro Hatsugai

The doubling of massless Dirac fermions on two-dimensional lattices is theoretically studied. It has been shown that the doubling of massless Dirac fermions on a lattice with broken chiral symmetry is topologically protected even when the Dirac cone is tilted. This is due to the generalized chiral symmetry defined for lattice systems, where such models can b

Laith Sakka, Kirshanthan Sundararajah, Ryan R. Newton, Milind Kulkarni

Applications in many domains are based on a series of traversals of tree structures, and fusing these traversals together to reduce the total number of passes over the tree is a common, important optimization technique. In applications such as compilers and render trees, these trees are heterogeneous: different nodes of the tree have different types. Unfortu

Thomas Produit, Pierre Walch, Guillaume Schimmel, Benoît Mahieu

We study the use of frequency upconversion schemes of near-IR picosecond laser pulses and compare their ability to guide and trigger electric discharges through filamentation in air. Upconversion, such as Second Harmonic Generation, is favorable for triggering electric discharges for given amount of available laser energy, even taking into account the losses

L. M. M. van den Bos, W. A. A. M. Bierbooms, A. Alexandre, B. Sanderse

A novel approach is proposed to reduce, compared to the conventional binning approach, the large number of aeroelastic code evaluations that are necessary to obtain equivalent loads acting on wind turbines. These loads describe the effect of long-term environmental variability on the fatigue loads of a horizontal-axis wind turbine. In particular Design Load

Samir Kundu, T. K. Rana, C. Bhattacharya, K. Banerjee

A large 4$π$ array of charged particle detectors has been developed at Variable Energy Cyclotron Centre to facilitate high resolution charged particle reaction and spectroscopy studies by detecting event-by-event the charged reaction products emitted in heavy ion reactions at energy $\sim$ 10-60 MeV/A. The forward part ($θ\sim \pm $ $7^{0}$ - $\pm 45^{0}$) o

Giuseppe Di Sciascio

During the last two decades Gamma-Ray Astronomy has emerged as a powerful tool to study cosmic ray physics. In fact, photons are not deviated by galactic or extragalactic magnetic fields so their directions bring the information of the production sites and are easier to detect than neutrinos. Thus the search for $γ$ primarily address in the framework of the

João Henrique Corrêa, Patrick Marques Ciarelli, Moises R. N. Ribeiro, Rodolfo da Silva Villaca

The detection of Denial of Service (DoS) attacks remains a challenge for the cloud environment, affecting a massive number of services and applications hosted by such virtualized infrastructures. Typically, in the literature, the detection of DoS attacks is performed solely by analyzing the traffic of packets in the network. This work advocates for the use o

Javier Lamar-Leon, Rocio Gonzalez-Diaz, Edel Garcia-Reyes

In this paper, we present an algorithm that computes the topological signature for a given periodic motion sequence. Such signature consists of a vector obtained by persistent homology which captures the topological and geometric changes of the object that models the motion. Two topological signatures are compared simply by the angle between the correspondin

Sourav Marik, Kapil Motla, Maneesha Varghese, K. P. Sajilesh

High entropy alloys (HEAs) are the new class of materials with an attractive combination of tunable mechanical and physicochemical properties. They crystallize mainly in cubic structures, however, for practical applications, HEAs with hexagonal close-packed (hcp) structure are highly desirable in connection to their in general high hardness. Herein, we repor

Takuma Kogo, Masanori Tsujikawa, Yukihiro Kiuchi, Atsushi Nishino

This paper proposes a methodology of model predictive control for alleviating shallow drowsiness of office workers and thus improving their productivity. The methodology is based on dynamically scheduling setting values for air conditioning and lighting to minimize drowsiness level of office workers on the basis of a prediction model that represents the rela

Zhenbang Li, Caifeng Liu

The Cauchy problem of the Cahn-Hilliard equations is studied in three-dimensional space. Firstly, we construct its approximate fourth-order parabolic equation, obtaining the existence of solutions by the Aubin-Lions's compactness lemma. Furthermore, we prove the uniqueness of the solution. Then, the global well-posedness is demonstrated by using energy e

Farrukh Mukhamedov, Chin Hee Pah, Hakim Jamil, Muzaffar Rahmatullaev

In this paper, we consider the $λ$-model with nearest neighbor interactions and with competing Potts interactions on the Cayley tree of order-two. We notice that if $λ$-function is taken as a Potts interaction function, then this model contains as a particular case of Potts model with competing interactions on Cayley tree. In this paper, we first describe al

Yerlan Amanbek, Gurpreet Singh, Gergina Pencheva, Mary F. Wheeler

In the flow and transport numerical simulation, mesh adaptivity strategy is important in reducing the usage of CPU time and memory. The refinement based on the pressure error estimator is commonly-used approach without considering the flux error which plays important role in coupling flow and transport systems. We derive a posteriori error estimators for Enh

Chu Wang, Lei Tang, Shujun Bian, Da Zhang

For a product of interest, we propose a search method to surface a set of reference products. The reference products can be used as candidates to support downstream modeling tasks and business applications. The search method consists of product representation learning and fingerprint-type vector searching. The product catalog information is transformed into

E. H. Coldebella, E. F. Chagas, A. P. Albuquerque, R. J. Prado

We report an experimental study of the bimagnetic nanocomposites CoFe2/CoFe2O4.The precursor material, CoFe2O4 was prepared using the conventional stoichiometric combustion method. The nanocomposite CoFe2/CoFe2O4 was obtained by total reduction of CoFe2O4 using a thermal treatment at 350oC in H2 atmospheres following a partial oxidation in O2 atmospheres at

P. Hartigan, R. Holcomb, A. Frank

We have used the Hubble Space Telescope to acquire new broad-band and narrow-band images of the optical line emission and red continuum associated with the HH 7-11 stellar jet in the NGC 1333 star formation region. Combining the new narrow-band images of H$α$, [O~I] $λ$6300 and [S II] $λ$6716 allows us to measure electron densities and excitations at each po

Jon Hoffman

Neural Networks accomplish amazing things, but they suffer from computational and memory bottlenecks that restrict their usage. Nowhere can this be better seen than in the mobile space, where specialized hardware is being created just to satisfy the demand for neural networks. Previous studies have shown that neural networks have vastly more connections than

Hang Zhao, Chuang Gan, Wei-Chiu Ma, Antonio Torralba

Sounds originate from object motions and vibrations of surrounding air. Inspired by the fact that humans is capable of interpreting sound sources from how objects move visually, we propose a novel system that explicitly captures such motion cues for the task of sound localization and separation. Our system is composed of an end-to-end learnable model called

G. Gallina, F. Retiere, P. Giampa, J. Kroeger

Silicon Photo-Multipliers (SiPMs) are detectors sensitive to single photons that are used to detect scintillation and Cherenkov light in a variety of physics and medical-imaging applications. SiPMs measure single photons by amplifying the photo-generated carriers (electrons or holes) via a Geiger-mode avalanche. The Photon Detection Efficiency (PDE) is the c

Adam F. Kowalski, Karel Schrijver, Valentin Martinez Pillet, Serena Criscuoli

We describe how the accurate characterization of exoplanetary atmospheres in the ELT and JWST era will inevitably require taking into consideration the stellar inhomogeneities caused by convection and magnetic fields. The existing evidence that demonstrates the mixture of stellar and planetary signatures in observed transiting spectra is presented. Finally,

José Villa-Morales

Let $f$ be a real-valued function defined on $\mathbb{R}$, with $f(0) \neq 0$ and which is not constant in non empty open intervals. We prove the equations \begin{equation}\label{edif} \left\{ \begin{array}{rcll} (-Δ)^{s}u & = & f(u), & \text{in }B_{1}, \\ u & = & 0, & \text{in }B_{1}^{c}, \end{array} \right. \end{equation} where $(-Δ)^{s}$ is the $s$-fracti

Heybetkulu Mustafayev

Let $A,$ $T$ and $B$ be bounded linear operators on a Banach space. This paper is concerned mainly with finding some necessary and sufficient conditions for convergence in operator norm of the sequences $\left\{ A^{n}TB^{n}\right\} $ and $\left\{ \frac{1}{n}\sum_{i=0}^{n-1}A^{i}TB^{i}% \right\} $. These results are applied to the Toeplitz, composition and mo

Adrian Huerta, Taras Bryk, Andrij Trokhymchuk

Molecular dynamics computer simulations of collective excitations in a system of hard disks confined to a narrow channel of the specific width, that resembles 2D triangular lattice at disk close packing, are performed. We found that transverse excitations, which for hard-disk system are absent in the limit of 1D and are of acoustic nature in the limit of 2D,

G. Ponti, F. Hofmann, E. Churazov, M. R. Morris

Evidence has increasingly mounted in recent decades that outflows of matter and energy from the central parsecs of our Galaxy have shaped the observed structure of the Milky Way on a variety of larger scales. On scales of ~15 pc, the Galactic centre has bipolar lobes that can be seen in both X-rays and radio, indicating broadly collimated outflows from the c

Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell

Learning good feature embeddings for images often requires substantial training data. As a consequence, in settings where training data is limited (e.g., few-shot and zero-shot learning), we are typically forced to use a generic feature embedding across various tasks. Ideally, we want to construct feature embeddings that are tuned for the given task. In this

Quan M. Bui, Daniel Osei-Kuffuor, Nicola Castelletto, Joshua A. White

Simulation of multiphase poromechanics involves solving a multi-physics problem in which multiphase flow and transport are tightly coupled with the porous medium deformation. To capture this dynamic interplay, fully implicit methods, also known as monolithic approaches, are usually preferred. The main bottleneck of a monolithic approach is that it requires s

Rodrigo A. Ricco, Bruno O. S. Teixeira

In subspace identification, prior information can be used to constrain the eigenvalues of the estimated state-space model by defining corresponding LMI regions. In this paper, first we argue on what kind of practical information can be extracted from historical data or step-response experiments to possibly improve the dynamical properties of the correspondin

François Gay-Balmaz, Hiroaki Yoshimura

A variational formulation for nonequilibrium thermodynamics was recently proposed in \cite{GBYo2017a,GBYo2017b} for both discrete and continuum systems. This formulation extends the Hamilton principle of classical mechanics to include irreversible processes. In this paper, we show that this variational formulation yields a constructive and systematic way to

Melissa L. Graham, Danny Milisavljevic, Armin Rest, J. Craig Wheeler

The Large Synoptic Survey Telescope (LSST) will open a discovery frontier for faint and fast transients with its ability to detect variable flux components down to $\sim$24.5 mag in a $\sim$30 second exposure. Spectroscopic follow-up of such phenomena - which are necessary for understanding the physics of stellar explosions - can require a rapid response and

V. V. Sagun, K. A. Bugaev, A. I. Ivanytskyi

Using the model of hexagonal clusters we express the surface, curvature and Gauss curvature coefficients of the nuclear binding energy in terms of its bulk coefficient. Using the derived values of these coefficients and a single fitting parameter we are able to reasonably well describe the experimental binding energies of nuclei with more than 100 nucleons.

Pierre Finnimore, Elisabeth Fritzsch, Daniel King, Alison Sneyd

Complex Word Identification (CWI) is the task of identifying which words or phrases in a sentence are difficult to understand by a target audience. The latest CWI Shared Task released data for two settings: monolingual (i.e. train and test in the same language) and cross-lingual (i.e. test in a language not seen during training). The best monolingual models

Alain Hecq, Li Sun

We propose a model selection criterion to detect purely causal from purely noncausal models in the framework of quantile autoregressions (QAR). We also present asymptotics for the i.i.d. case with regularly varying distributed innovations in QAR. This new modelling perspective is appealing for investigating the presence of bubbles in economic and financial t

Lukas Ramlow, Jakub Sawicki, Anna Zakharova, Jaroslav Hlinka

We analyze partial synchronization patterns in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in healthy human subjects. We report a dynamical asymmetry between the hemispheres, induced by the natural structural asymmetry. We show that the dynamical asymmetry can be enhanced by introducing the inter-hemispheric coupl

Márton Véges, András Lőrincz

The common approach to 3D human pose estimation is predicting the body joint coordinates relative to the hip. This works well for a single person but is insufficient in the case of multiple interacting people. Methods predicting absolute coordinates first estimate a root-relative pose then calculate the translation via a secondary optimization task. We propo

Taran Driver, Ruth Ayers, Rüdiger Pipkorn, Bridgette Cooper

Mass spectrometry (MS) is used widely in biomolecular structural analysis and is particularly dominant in the study of proteins. Despite its considerable power, state-of-the-art protein MS frequently suffers from limited reliability of spectrum-to-structure assignments. This could not be solved fully by the dramatic increase in mass accuracy and resolution o

Chris Nolting, T. W. Jones, Brian O'Neill, P. J. Mendygral

We report from a study utilizing 3D MHD simulations, including cosmic-ray electrons, of the interactions between radio galaxies (RGs) and dynamically active ICMs. Here we consider interactions involving plane ICM shocks having Mach numbers 2--4 and their normals aligned with steady, active bipolar RG jets penetrating uniform, stationary ICMs. Shock impact di

John Yu

We construct a Taylor-Wiles system using a family of $p$-adically completed modular Jacobians over suitable Hecke algebras and prove that certain $p$-adically completed Mordell-Weil groups of these Jacobians is free of finite rank over a Hecke algebra.

Keren Sharon, Matthew B. Bayliss, Håkon Dahle, Samuel J. Dunham

We present strong gravitational lensing models for 37 galaxy clusters from the SDSS Giant Arcs Survey. We combine data from multi-band Hubble Space Telescope WFC3imaging, with ground-based imaging and spectroscopy from Magellan, Gemini, APO, and MMT, in order to detect and spectroscopically confirm new multiply-lensed background sources behind the clusters.

Syed Waqas Zamir, Aditya Arora, Salman Khan, Fahad Shahbaz Khan

In low-light conditions, a conventional camera imaging pipeline produces sub-optimal images that are usually dark and noisy due to a low photon count and low signal-to-noise ratio (SNR). We present a data-driven approach that learns the desired properties of well-exposed images and reflects them in images that are captured in extremely low ambient light envi

Bingyu Wang, Li Chen, Wei Sun, Kechen Qin

Extreme Multi-label classification (XML) is an important yet challenging machine learning task, that assigns to each instance its most relevant candidate labels from an extremely large label collection, where the numbers of labels, features and instances could be thousands or millions. XML is more and more on demand in the Internet industries, accompanied wi

Ori Shapira, David Gabay, Yang Gao, Hadar Ronen

Conducting a manual evaluation is considered an essential part of summary evaluation methodology. Traditionally, the Pyramid protocol, which exhaustively compares system summaries to references, has been perceived as very reliable, providing objective scores. Yet, due to the high cost of the Pyramid method and the required expertise, researchers resorted to

Matheus Koveroff Bellini, Vinicius de Oliveira Rodrigues, Artur Hideyuki Tomita

We prove that if $p$ is a selective ultrafilter then ${\mathbb Q}^{(κ)}$ has a $p$-compact group topology without non-trivial convergent sequences, for each infinite cardinal $κ=κ^ω$. In particular, this gives the first arbitrarily large examples of countably compact groups without non-trivial convergent sequences that are torsion-free.

Dmytro Ageyev, Lyudmyla Kirichenko, Tamara Radivilova, Maksym TawalbehRadivilova

In this paper, the problem of load balancing in network intrusion detection system is considered. Load balancing method based on work of several components of network intrusion detection system and on the analysis of multifractal properties of incoming traffic is proposed. The proposed method takes into account a degree of multifractality for calculation of

Igor Ivanisenko, Lyudmyla Kirichenko, Tamara Radivilova

The work presents results of numerical study of self-similar properties of additive data traffic. It is shown that the value of Hurst exponent of total stream is determined by the maximum value of Hurst exponent of summed streams and the ratio of variation coefficient of stream with maximum Hurst exponent and other ones.

Igor Ivanisenko, Tamara Radivilova

The classification of the most used load balancing algorithms in distributed systems (including cloud technology, cluster systems, grid systems) is described. Comparative analysis of types of the load balancing algorithms is conducted in accordance with the classification, the advantages and drawbags of each type of the algorithms are shown. Performance indi

Bing Yu, Xiaojing Xing, Agus Sudjianto

As is known, an option price is a solution to a certain partial differential equation (PDE) with terminal conditions (payoff functions). There is a close association between the solution of PDE and the solution of a backward stochastic differential equation (BSDE). We can either solve the PDE to obtain option prices or solve its associated BSDE. Recently a d

Fan Liu, Christos Masouros, Hugh Griffiths

In this paper, we focus on constant-modulus waveform design for the dual use of radar target detection and cellular transmission. As the MIMO radar typically transmits orthogonal waveforms to search potential targets, we aim at jointly minimizing the downlink multi-user interference and the non-orthogonality of the transmitted waveform. Given the non-convexi

Chris T. Richardson, Mugdha S. Polimera, Sheila J. Kannappan, Amanda J. Moffett

Metal poor dwarf galaxies in the local universe, such as those found in the RESOLVE galaxy survey, often produce high [O III]/H\b{eta} ratios close to the star forming demarcation lines of the diagnostic BPT diagram. Modeling the emission from these galaxies at lower metallicities generally underpredicts this line ratio, which is typically attributed to a de

Rocio Kiman, Sarah J. Schmidt, Ruth Angus, Kelle L. Cruz

We present a sample of 74,216 M and L dwarfs constructed from two existing catalogs of cool dwarfs spectroscopically identified in the Sloan Digital Sky Survey (SDSS). We cross-matched the SDSS catalog with Gaia DR2 to obtain parallaxes and proper motions and modified the quality cuts suggested by the Gaia Collaboration to make them suitable for late-M and L

Yan-Fei Li, Ren-Tong Guo, Rashid Shaisultanov, Karen Z. Hatsagortsyan

Impacts of spin-polarization of an ultrarelativistic electron beam head-on colliding with a strong laser pulse on emitted photon spectra and electron dynamics have been investigated in the quantum radiation regime. We simulate photon emissions quantum mechanically and electron dynamics semiclassically via taking spin-resolved radiation probabilities in the l

Francois Hennecart, Gyan Prakash, E. Pramod

Besides various asymptotic results on the concept of sum-product bases in $\mathbb{N}_0$, we consider by probabilistic arguments the existence of thin sets $A,A'$ of integers such that $AA+A=\mathbb{N}_0$ and $A'A'+A'A'=\mathbb{N}_0$.

Anna Lisa Amadori, Francesca Gladiali

In this paper we consider the Hénon problem in the unit disc with Dirichlet boundary conditions. We study the asymptotic profile of least energy and nodal least energy radial solutions and then deduce the exact computation of their Morse index for large values of the exponent p. As a consequence of this computation a multiplicity result for positive and noda

Zhuqing Jia, Syed A. Jafar

The problem of private information retrieval with graph-based replicated storage was recently introduced by Raviv, Tamo and Yaakobi. Its capacity remains open in almost all cases. In this work the asymptotic (large number of messages) capacity of this problem is studied along with its generalizations to include arbitrary $T$-privacy and $X$-security constrai

Murat Kologlu, Petr Kravchuk, David Simmons-Duffin, Alexander Zhiboedov

We study propagation of a probe particle through a series of closely situated gravitational shocks. We argue that in any UV-complete theory of gravity the result does not depend on the shock ordering - in other words, coincident gravitational shocks commute. Shock commutativity leads to nontrivial constraints on low-energy effective theories. In particular,

Benjamin D. Oppenheimer, Jonathan J. Davies, Robert A. Crain, Nastasha A. Wijers

Davies et al. (2019) established that for L^* galaxies the fraction of baryons in the circumgalactic medium (CGM) is inversely correlated with the mass of their central supermassive black holes (BHs) in the EAGLE hydrodynamic simulation. The interpretation is that, over time, a more massive BH has provided more energy to transport baryons beyond the virial r

Kyle Cranmer, Siavash Golkar, Duccio Pappadopulo

We introduce two methods for estimating the density matrix for a quantum system: Quantum Maximum Likelihood and Quantum Variational Inference. In these methods, we construct a variational family to model the density matrix of a mixed quantum state. We also introduce quantum flows, the quantum analog of normalizing flows, which can be used to increase the exp

Mohammadtaher Safarzadeh, Abraham Loeb

We study the recently observed JellyFish galaxies (JFGs), which are found to have their gas content ram-pressure stripped away in galaxy clusters. These galaxies are observed to have an enhanced star formation rate of about 0.2 dex compared with a control sample of the same stellar mass in their disks. We model the increase in the star formation efficiency a

Andrea Vittino, Philipp Mertsch, Henning Gast, Stefan Schael

Until fairly recently, it was widely accepted that local cosmic ray spectra were largely featureless power laws, containing limited information on their acceleration and transport. This viewpoint is currently being revised in the light of evidence for a variety of spectral breaks in the fluxes of cosmic ray nuclei. Here, we focus on cosmic ray electrons and

Tushar Mondal, Banibrata Mukhopadhyay

The $Fermi$ blazar observations show a strong correlation between $γ$-ray luminosities and spectral indices. BL Lac objects are less luminous with harder spectra than flat-spectrum radio quasars (FSRQs). Interestingly FSRQs are evident to exhibit a Keplerian disc component along with a powerful jet. We compute the jet intrinsic luminosities by beaming correc

D. Milisavljevic, R. Margutti, R. Chornock, A. Rest

Supernovae are among the most powerful and influential explosions in the universe. They are also ideal multi-messenger laboratories to study extreme astrophysics. However, many fundamental properties of supernovae related to their diverse progenitor systems and explosion mechanisms remain poorly constrained. Here we outline how late-time spectroscopic observ

Hamid Ebrahimi, Hosein Haghi, Pouria Khalaj, Akram Hasani Zonoozi

We study the dynamical evolution of star clusters on eccentric orbits using a semi-analytical approach. In particular we adapt and extend the equations of EMACSS code, introduced by Gieles et al. (2014), to work with eccentric orbits. We follow the evolution of star clusters in terms of mass, half-mass radius, core radius, Jacobi radius and the total energy

K. Arur, T. J. Maccarone

We examine the nonlinear variability of quasi-periodic oscillations (QPOs) using the bicoherence, a measure of phase coupling at different Fourier frequencies. We analyse several observations of RXTE/PCA archival data of the black hole binary GX 339-4 which show QPOs. In the type C QPOs, we confirm the presence of the 'hypotenuse' pattern where there

Cristina Garcia-Vergara, Joseph F. Hennawi, L. Felipe Barrientos, Fabrizio Arrigoni Battaia

The strong observed clustering of $z>3.5$ quasars indicates they are hosted by massive ($M_{\rm{halo}}\gtrsim10^{12}\,h^{-1}\,\rm{M_{\odot}}$) dark matter halos. Assuming quasars and galaxies trace the same large-scale structures, this should also manifest as strong clustering of galaxies around quasars. Previous work on high-redshift quasar environments, mo

Thomas G. Wilson, Jay Farihi, Boris T. Gänsicke, Andrew Swan

This paper presents combined ${\it Spitzer}$ IRAC and ${\it Hubble}$ COS results for a double-blind survey of 195 single and 22 wide binary white dwarfs for infrared excesses and atmospheric metals. The selection criteria include cooling ages in the range 9 to 300 Myr, and hydrogen-rich atmospheres so that the presence of atmospheric metals can be confidentl

Mansoureh Hosseinpour, Hassan Hassanabadi, Marc de Montigny

We examine the effects of gravitational fields produced by topological defects on a Dirac field and a Dirac oscillator in a spinning cosmic string spacetime. We obtain the eigenfunctions and the energy levels of the relativistic field in that background and consider the effect of various parameters, such as the frequency of the rotating frame, the oscillator

Antonio Capolupo

The analysis of the total and geometric phases generated by the neutrino oscillation shows that these phases for Majorana neutrinos are depending on the representation of the mixing matrix and they are different from those of Dirac neutrinos.

Jordan Franks

We consider the efficient use of an approximation within Markov chain Monte Carlo (MCMC), with subsequent importance sampling (IS) correction of the Markov chain inexact output, leading to asymptotically exact inference. We detail convergence and central limit theorems for the resulting MCMC-IS estimators. We also consider the case where the approximate Mark

M. Sharif, Arfa Waseem

This paper is devoted to the study of stellar evolution of compact objects whose energy density and pressure of the fluid are interlinked by means of MIT bag model and a realistic polytropic equation of state in the scenario of $f(R,T,Q)$ gravity, where $Q=R_{ab}T^{ab}$. We derive the field equations as well as the hydrostatic equilibrium equation and analyz

Matthias Ehrendorfer, Juergen-Albrecht Fassmann, Juergen Mangler, Stefanie Rinderle-Ma

Currently, data collection on the shop floor is based on individual resources such as machines, robots, and Autonomous Guided Vehicles (AGVs). There is a gap between this approach and manufacturing orchestration software that supervises the process of creating single products and controls the ressources' interactions. This creates the need to save resour

Unnat Jain, Luca Weihs, Eric Kolve, Mohammad Rastegari

Collaboration is a necessary skill to perform tasks that are beyond one agent's capabilities. Addressed extensively in both conventional and modern AI, multi-agent collaboration has often been studied in the context of simple grid worlds. We argue that there are inherently visual aspects to collaboration which should be studied in visually rich environme

Iou-Jen Liu, Jian Peng, Alexander G. Schwing

A zoo of deep nets is available these days for almost any given task, and it is increasingly unclear which net to start with when addressing a new task, or which net to use as an initialization for fine-tuning a new model. To address this issue, in this paper, we develop knowledge flow which moves 'knowledge' from multiple deep nets, referred to as t

Idan Schwartz, Alexander Schwing, Tamir Hazan

The recently proposed audio-visual scene-aware dialog task paves the way to a more data-driven way of learning virtual assistants, smart speakers and car navigation systems. However, very little is known to date about how to effectively extract meaningful information from a plethora of sensors that pound the computational engine of those devices. Therefore,

Ben-Hur Francisco Cardoso, Sebastián Gonçalves, José Roberto Iglesias

Simple agent based exchange models are a commonplace in the study of wealth distribution in an artificial economy. Generally, in a system that is composed of many agents characterized by their wealth and risk-aversion factor, two agents are selected sequentially and randomly to exchange wealth, allowing for its redistribution. Here we analyze how the effect

Xizhou Zhu, Dazhi Cheng, Zheng Zhang, Stephen Lin

Attention mechanisms have become a popular component in deep neural networks, yet there has been little examination of how different influencing factors and methods for computing attention from these factors affect performance. Toward a better general understanding of attention mechanisms, we present an empirical study that ablates various spatial attention

Hengduo Li, Bharat Singh, Mahyar Najibi, Zuxuan Wu

We provide a detailed analysis of convolutional neural networks which are pre-trained on the task of object detection. To this end, we train detectors on large datasets like OpenImagesV4, ImageNet Localization and COCO. We analyze how well their features generalize to tasks like image classification, semantic segmentation and object detection on small datase

Adrian Bulat, Georgios Tzimiropoulos, Jean Kossaifi, Maja Pantic

Big neural networks trained on large datasets have advanced the state-of-the-art for a large variety of challenging problems, improving performance by a large margin. However, under low memory and limited computational power constraints, the accuracy on the same problems drops considerable. In this paper, we propose a series of techniques that significantly

Luigi Di Tacchio, Zulkar Nine, Tevfik Kosar, Fatih M. Bulut

The energy footprint of global data movement has surpassed 100 terawatt hours, costing more than 20 billion US dollars to the world economy. Depending on the number of switches, routers, and hubs between the source and destination nodes, the networking infrastructure consumes 10% - 75% of the total energy during active data transfers, and the rest is consume

Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart

To facilitate the analysis of human actions, interactions and emotions, we compute a 3D model of human body pose, hand pose, and facial expression from a single monocular image. To achieve this, we use thousands of 3D scans to train a new, unified, 3D model of the human body, SMPL-X, that extends SMPL with fully articulated hands and an expressive face. Lear

Prabhu Kaliyammal Thiruvasagam, Vijeth J Kotagi, C Siva Ram Murthy

Although network functions virtualization and software-defined networking offer many dynamic features such as flexibility, scalability, and programmability for easy provisioning of services at a lesser cost and time through service function chaining, it introduces new challenges in terms of reliability, availability, and latency of services. Particularly, so

Sayantan Mondal, Subhajit Acharya, Biman Bagchi

Spherical confinement can alter the properties of a dipolar fluid in several different ways. In an atomistic molecular dynamics simulation study of two different dipolar liquids (SPC/E water and a model Stockmayer fluid) confined to nanocavities of different radii ranging from Rc=1nm to 4nm, we find that the Kirkwood correlation factor remains surprisingly s

Claudia Draxl, Matthias Scheffler

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community

Brian J. Williams, Katie Auchettl, Carles Badenes, Daniel Castro

This is a white paper submitted in response to the call from the Astro2020 Decadal Survey Committee. We outline the scientific progress that will be made in the next few decades in the study of supernova remnants in the X-ray band, using observatories like Athena, Lynx, and AXIS.

Joseph E. Gaudio, Travis E. Gibson, Anuradha M. Annaswamy, Michael A. Bolender

This paper demonstrates many immediate connections between adaptive control and optimization methods commonly employed in machine learning. Starting from common output error formulations, similarities in update law modifications are examined. Concepts in stability, performance, and learning, common to both fields are then discussed. Building on the similarit

Bart Cleuren, Karel Proesmans

The concept of impedance, which characterises the current response to a periodical driving, is introduced in the context of stochastic transport. In particular, we calculate the impedance for an exactly solvable model, namely the stochastic transport of particles through a single-level quantum dot.

Noga Agmon, Asaf Shabtai, Rami Puzis

The Internet of things (IoT) has become an integral part of our life at both work and home. However, these IoT devices are prone to vulnerability exploits due to their low cost, low resources, the diversity of vendors, and proprietary firmware. Moreover, short range communication protocols (e.g., Bluetooth or ZigBee) open additional opportunities for the lat

M. Gehrke, S. J. v. Gool

It has long been known in universal algebra that any distributive sublattice of congruences of an algebra which consists entirely of commuting congruences yields a sheaf representation of the algebra. In this paper we provide a generalisation of this fact and prove a converse of the generalisation. To be precise, we exhibit a one-to-one correspondence (up to

Marco Antonio López

In the present work we establish a Bowen-type formula for the Hausdorff dimension of shrinking-target sets for non-autonomous conformal iterated function systems in arbitrary dimensions and satisfying certain conditions. In the case of dimension 1 we also investigate non-linear perturbations of linear systems and obtain sufficient conditions under which the

Juan Leon Alcazar, Maria A. Bravo, Ali K. Thabet, Guillaume Jeanneret

Instance-level video segmentation requires a solid integration of spatial and temporal information. However, current methods rely mostly on domain-specific information (online learning) to produce accurate instance-level segmentations. We propose a novel approach that relies exclusively on the integration of generic spatio-temporal attention cues. Our strate

Mohamed Baza, Mahmoud Nabil, Niclas Bewermeier, Kemal Fidan

In this paper, we propose a Sybil attack detection scheme using proofs of work and location. The idea is that each road side unit (RSU) issues a signed time-stamped tag as a proof for the vehicle's anonymous location. Proofs sent from multiple consecutive RSUs is used to create vehicle trajectory which is used as vehicle anonymous identity. Also, one RSU

Leon A. Wilson, Yoann Senin, Yibin Wang, Václav Rajlich

Software change is the basic task of software evolution and maintenance. Phased Model for Software Change (PMSC) is a process model for software changes that localize in the code. It consists of several phases that cover both program comprehension and code modifications. This paper presents an empirical study of an enactment of PMSC, enhanced by the use of t

Sungsoo Ahn, Shell Xu Hu, Andreas Damianou, Neil D. Lawrence

Transferring knowledge from a teacher neural network pretrained on the same or a similar task to a student neural network can significantly improve the performance of the student neural network. Existing knowledge transfer approaches match the activations or the corresponding hand-crafted features of the teacher and the student networks. We propose an inform

Vahid Mohammadi, Mehdi Dehghan, Amirreza Khodadadian, Thomas Wick

In this work, we apply two meshless methods for the numerical solution of the time-dependent transport equation defined on the sphere in spherical coordinates. The first technique, which was introduced by Mirzaei (BIT Numerical Mathematics, 54 (4) 1041-1063, 2017) in Cartesian coordinates is a generalized moving least squares approximation, and the second on

Kechen Qin, Cheng Li, Virgil Pavlu, Javed A. Aslam

We present an adaptation of RNN sequence models to the problem of multi-label classification for text, where the target is a set of labels, not a sequence. Previous such RNN models define probabilities for sequences but not for sets; attempts to obtain a set probability are after-thoughts of the network design, including pre-specifying the label order, or re

Nicolás E. Kuschinski, J. Andrés Christen

In linear models it is common to have situations where several regression coefficients are zero. In these situations a common tool to perform regression is a variable selection operator. One of the most common such operators is the LASSO operator, which promotes point estimates which are zero. The LASSO operator and similar approaches, however, give little i

Tim Bastian, Bin Chen, Dale Gary, Gregory Fleishman

Identification of the mechanisms responsible for heating the solar chromosphere and corona remains an outstanding problem, one of great relevance to late-type stars as well. There has been tremendous progress in the past decade, largely driven by new instruments, new observations, and sophisticated modeling efforts. Despite this progress, gaps remain. We bri

Aaron J. Rosengren, Despoina K. Skoulidou, Kleomenis Tsiganis, George Voyatzis

We have carried out a numerical investigation of the coupled gravitational and non-gravitational perturbations acting on Earth satellite orbits in an extensive grid, covering the whole circumterrestrial space, using an appropriately modified version of the SWIFT symplectic integrator, which is suitable for long-term (120 years) integrations of the non-averag

Ryuta Iwazaki, Naoto Tsuji, Shintaro Hoshino

The photo-excited state associated with superconducting fluctuation above the superconducting critical temperature $T_c$ is studied based on the time-dependent Ginzburg-Laundau approach. The excited state is created by an electric-field pulse and is probed by a weak secondary external field, which is treated by the linear response theory mimicking pump-probe

Tim Bastian, Hazel Bain, Bin Chen, Dale Gary

The Sun is an active star that can have a direct impact on the Earth, its magnetosphere, and the technological infrastructure on which modern society depends. Among the phenomena that drive "space weather" are fast solar wind streams and co-rotating interaction regions, solar flares, coronal mass ejections, the shocks they produce, and the energetic

Yuqing Wang, Mika Mäntylä, Sigrid Eldh, Jouni Markkula

Test automation is important in software industry but self-assessment instruments for assessing its maturity are not sufficient. The two objectives of this study are to synthesize what an organization should focus to assess its test automation; develop a self-assessment instrument (a survey) for assessing test automation maturity and scientifically evaluate